Practical classification problems often posses a skewed label distribution \(\mathbb {P}( y )\) .
This problem of learning under class imbalance is a classical area of study [1]}, [2]}, [3]},
which
has received renewed interest in the context of neural models
in the area of long-tail learning [4]}, [5]}, [6]}, [7]}.
The core challenge in such settings is ensuring that rare labels are not systematically misclassified,
owing to their limited representation in the training data.
